为药物研发设计的模型管理平台，支持多模型协同与科学化治理。
Model Gateway: Management Platform for Model-Driven Drug Discovery
- 构建云原生平台实现多模型异步编排与版本控制。
- 管理超200个模型，覆盖小分子、肽类和抗体等类型。
- 适合药企研发团队使用，支持从设计到测试全流程自动化。
药物研发需要超越通用机器学习运维（MLOps）的基础设施：包括推理时多模型组合进行多参数优化（MPO）、无序列化机器学习成果的物理模型版本管理、企业化合物库的预计算，以及围绕科研组织结构而非通用权限的治理机制。现有商业或开源平台无法同时满足这些需求。本文提出Model Gateway，一个面向药物发现管线的云端模型管理平台，提供集中式版本控制、制药业结构化治理、异步执行、共识模型编排、自动重训练及统一API服务，支持分子设计套件和大语言模型（LLM）代理等异构客户端。该平台已在礼来公司投入生产，管理超过200个已部署模型，涵盖小分子、肽类和抗体等多种模态，并服务于研发全周期中五个以上下游应用。
原文摘要 · Abstract (English)
Pharmaceutical drug discovery demands machine learning (ML) infrastructure that goes beyond general-purpose Machine Learning Operations (MLOps): inference-time composition of multiple models for multi-parameter optimization (MPO), version management for physics-based models without serialized ML artifacts, enterprise compound library precomputation, and governance structured around scientific organizational units rather than generic access controls. No existing commercial or open-source platform simultaneously addresses this full set of requirements. This paper presents the Model Gateway, a cloud-based platform for managing machine learning and scientific computational models across drug discovery pipelines, providing centralized version control, pharma-structured governance, asynchronous execution, consensus model orchestration, automated retraining, and a unified application programming interface (API) service for heterogeneous clients including molecular design suites and Large Language Model (LLM) agents. In production at Eli Lilly, the platform governs more than 200 deployed models spanning small molecule, peptide, and antibody modalities and serves more than five downstream applications across all phases of the Design-Make-Test-Analyze cycle.
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